City Science Lab San Francisco × MIT Media Lab City Science

Public Safety Pulse

Measuring everyday safety perception in San Francisco
"Safety isn't just a statistic; it's a feeling you hold when you're walking down the street."
— Daniel Lurie, Mayor of San Francisco, Inauguration Speech, January 2025
↓45%
Crime
2019 → 2025
63%
Feel Safe (Day)
2023 City Survey
36%
Feel Safe (Night)
2023 City Survey
626,911
311 Disorder Cases
Safety-filtered, 12 months
85,804
SFPD Incidents
12 months

The Perception Gap in Twenty-Seven Years of Data

Source: SF Controller's Office, City Performance Survey, 1996–2023. General satisfaction (red) fell to an all-time low of 2.98 in 2023. Crime has continued falling since.

Perception is shifting — but we can only see it in expensive one-off polls

78%
feel safe downtown during the day
43%
say SF is on the right track (up from 22% in 2024)
↓34%
fewer voters say crime has gotten worse
↓25%
fewer say street behavior is worse

Source: SF Chamber of Commerce CityBeat 2025 Poll, sponsored by United Airlines

Why the Gap Persists

Total reported crime fell 44.9% from 2019 through 2025 — from 119,177 incidents to 65,707. Every single one of the city's ten police districts recorded a decline. Yet the City Survey hit its lowest safety score since 1996.

The answer lies in composition. Larceny theft — car break-ins, shoplifting, package theft — drives roughly 60% of the statistical decline but is most susceptible to reporting changes. Meanwhile, the visible markers that shape how a street feels — encampments, needles, graffiti, aggressive behavior — are captured in 311 data, not crime data. The gap between what the statistics say and what people experience is the problem Public Safety Pulse solves.

How Does Each Block Feel?

250,000 geocoded 311 disorder reports rendered at block level. Taller, hotter columns = more reports about encampments, street cleaning, graffiti, and needles — a proxy for how unsafe an area feels. Hit play to watch hotspots shift across 24 hours.

Viewing
All Day
Low
Medium
High
Critical

What's Driving the Signal?

Methodology: Each hexagon aggregates geocoded reports within ~80m radius. Height and color = report density. Data: DataSF Socrata API, 12-month window. vw6y-z8j6 311 Cases wg3w-h783 SFPD Incidents

When Does the City Feel Unsafe?

The same block feels different at noon versus midnight. This is the variation the City Survey can't capture — it asks one question, once every two years. Public Safety Pulse captures it in 4-hour windows, every day, at block level.

Hourly Distribution of 311 Disorder Reports

☀️ Daytime (7am – 7pm)
🌙 Nighttime (9pm – 5am)
Why This Matters for Phase 1
Public Safety Pulse would capture this time-of-day variation at block level — telling you not just where people feel unsafe, but when. That's the difference between deploying an ambassador team to a neighborhood and deploying them to a specific intersection at 6pm on Thursdays.

Disorder vs Crime by Neighborhood

The Disorder–Crime Divergence shows where what people see (311 environmental reports) differs from the crime data. Neighborhoods with high divergence have a perception problem — they feel unsafe because of environmental conditions, not criminal danger. These are where cleaning, lighting, and ambassador programs have the highest ROI.

Monthly Trends

Everything you just saw is proxy data — our best guess.

311 only captures what people report. Crime data only captures what police file. Areas people avoid appear safe in the data. We need the actual signal.

What Phase 1 Unlocks

What We Have Now (Proxy)What Phase 1 Adds (Direct)
311 complaints — lagging, reporter biasDirect, in-the-moment perception
Crime incidents — only what gets reportedReal-time safety sentiment
Biennial survey — 2-year lag, neighborhood levelDaily signal, block level
Review text mining — business-adjacent onlyUniversal coverage via existing touchpoints
Foot traffic proxy — infers avoidanceDirectly asks: "How does this area feel?"

The Solution: Low-Friction Sentiment Capture

A single, optional question — "Right now, how does the surrounding area feel to you?" — delivered through existing digital touchpoints during normal daily activity. Comfortable / Neutral / Uncomfortable. Anonymous. Aggregated by place and time.

Offices & Buildings
Employee check-in via Envoy, workplace comms, visitor sign-in
Stores & Venues
Point of sale — Square, Toast, Clover. Also SNAP, Apple Pay, Google Wallet
Transit
BART / Muni, Uber / Lyft / Waymo, Google Maps, parking apps
Mobile & Location
AllTrails, Strava, Yelp, QR feedback kiosks in public spaces
$150–200K
Phase 1 Investment
6-month pilot
6 months
Pilot Duration
Define → Build → Capture → Evaluate
50K/mo
Response Target
Ramp from 5K initial

The Feedback Loop

Public Safety Pulse creates a powerful feedback loop: collect high-frequency ground truth on how safe people feel → feed it into a correlation engine that identifies which levers move perception → deploy targeted interventions (cleaning, lighting, ambassadors, music, signage) → measure the impact in near-real-time → optimize. This is how you turn data into measurably safer streets.

Partner with us to validate whether direct sentiment can fill the gap.

City Science Lab San Francisco × MIT Media Lab City Science

Public Safety Pulse — City Science Lab San Francisco × MIT Media Lab City Science
Data: DataSF Open Data Portal · SF City Performance Survey 2023 · CityBeat 2025 Poll · SFPD
vw6y-z8j6 wg3w-h783 ubvf-ztfx